Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.omega.2017.01.006
DC FieldValue
dc.titleThe two-dimensional vector packing problem with general costs
dc.contributor.authorQian Hu
dc.contributor.authorLijun Wei
dc.contributor.authorLim Leong Chye, Andrew
dc.date.accessioned2020-05-04T10:24:10Z
dc.date.available2020-05-04T10:24:10Z
dc.date.issued2018-01-01
dc.identifier.citationQian Hu, Lijun Wei, Lim Leong Chye, Andrew (2018-01-01). The two-dimensional vector packing problem with general costs. Omega 74 : 59-69. ScholarBank@NUS Repository. https://doi.org/10.1016/j.omega.2017.01.006
dc.identifier.issn0305-0483
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/167673
dc.description.abstractThe two-dimensional vector packing problem with general costs (2DVPP-GC) arises in logistics where shipping items of different weight and volume are packed into cartons before being transported by a courier company. In practice, the delivery cost of a carton of items is usually retrieved from a cost table. The costs may not preserve any known mathematical function since it could specify arbitrary price at any possible weight. Such a general pricing scheme meets a majority of real-world bin packing applications, where the price of delivery service is determined by many complicated and correlated factors. Compared to the classical bin packing problem and its variants, the 2DVPP-GC is more complex and challenging. To solve the 2DVPP-GC with minimizing the total cost, we propose a memetic algorithm to compute solutions of high quality. Fitness functions and improved operators are proposed to achieve effectiveness. Computational experiments on a variety of test instances show that the algorithm is competent to solve the 2DVPP-GC. In particular, optimal solutions are found in a second for all the test instances that have a known optimal solution.
dc.language.isoen
dc.publisherElsevier
dc.subjectApplication
dc.subjectBin packing
dc.subjectTwo-dimensional vector packing
dc.subjectGeneral costs
dc.subjectMemetic algorithm
dc.typeArticle
dc.contributor.departmentINDUSTRIAL SYSTEMS ENGINEERING AND MANAGEMENT
dc.description.doi10.1016/j.omega.2017.01.006
dc.description.sourcetitleOmega
dc.description.volume74
dc.description.page59-69
dc.published.statePublished
dc.grant.idNRF-RSS2016004
dc.grant.idR266000096133
dc.grant.idR266000096731
dc.grant.idR266000100646
dc.grant.fundingagencyNRF of Singapore
dc.grant.fundingagencyMOE
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